scholarly journals The response of the equatorial tropospheric ozone to the Madden–Julian Oscillation in TES satellite observations and CAM-chem model simulation

2014 ◽  
Vol 14 (21) ◽  
pp. 11775-11790 ◽  
Author(s):  
W. Sun ◽  
P. Hess ◽  
B. Tian
Keyword(s):  
Tropospheric Ozone ◽  
Large Scale ◽  
Transport Model ◽  
Model Simulation ◽  
General Pattern ◽  
Phase Speed ◽  
Satellite Observations ◽  
Madden Julian Oscillation ◽  
Dominant Form ◽  
Total Column Ozone

Abstract. The Madden–Julian Oscillation (MJO) is the dominant form of the atmospheric intra-seasonal oscillation, manifested by slow eastward movement (about 5 m s−1) of tropical deep convection. This study investigates the MJO's impact on equatorial tropospheric ozone (10° N–10° S) in satellite observations and chemical transport model (CTM) simulations. For the satellite observations, we analyze the Tropospheric Emission Spectrometer (TES) level-2 ozone profile data for the period of January 2004 to June 2009. For the CTM simulations, we run the Community Atmosphere Model with chemistry (CAM-chem) driven by the Goddard Earth Observing System Model, Version 5 (GEOS-5)-analyzed meteorological fields for the same data period as the TES measurements. Our analysis indicates that the behavior of the total tropospheric column (TTC) ozone at the intra-seasonal timescale is different from that of the total column ozone, with the signal in the equatorial region comparable with that in the subtropics. The model-simulated and satellite-measured ozone anomalies agree in their general pattern and amplitude when examined in the vertical cross section (the average spatial correlation coefficient among the eight phases is 0.63), with an eastward propagation signature at a similar phase speed as the convective anomalies (5 m s−1). The model ozone anomalies on the intra-seasonal timescale are about 5 times larger when lightning emissions of NOx are included in the simulation than when they are not. Nevertheless, large-scale advection is the primary driving force for the ozone anomalies associated with the MJO. The variability related to the MJO for ozone reaches up to 47% of the total variability (ranging from daily to interannual), indicating that the MJO should be accounted for in simulating ozone perturbations in the tropics.

scholarly journals The response of the equatorial tropospheric ozone to the Madden–Julian Oscillation in TES satellite observations and CAM-chem model simulation

2014 ◽  
Vol 14 (11) ◽  
pp. 16085-16122
Author(s):  
W. Sun ◽  
P. Hess ◽  
B. Tian
Keyword(s):  
Time Scale ◽  
Tropospheric Ozone ◽  
Large Scale ◽  
Transport Model ◽  
Model Simulation ◽  
General Pattern ◽  
Phase Speed ◽  
Satellite Observations ◽  
Madden Julian Oscillation ◽  
Total Column Ozone

Abstract. The Madden–Julian Oscillation (MJO) is the dominant form of the atmospheric intra-seasonal oscillation, manifested by slow eastward movement (about 5 m s−1) of tropical deep convection. This study investigates the MJO's impact on equatorial tropospheric ozone (10° N–10° S) in satellite observations and chemical transport model (CTM) simulations. For the satellite observations, we analyze the Tropospheric Emission Spectrometer (TES) level-2 ozone profile data for the period of January 2004 to June 2009. For the CTM simulations, we run the Community Atmosphere Model with chemistry (CAM-chem) driven by the GOES-5 analyzed meteorological fields for the same data period as the TES measurements. Our analysis indicates that the behavior of the Total Tropospheric Column (TTC) ozone at the intraseasonal time scale is different from that of the total column ozone, with the signal in the equatorial region comparable with that in the subtropics. The model simulated and satellite measured ozone anomalies agree in their general pattern and amplitude when examined in the vertical cross section (the average spatial correlation coefficient among the 8 phases is 0.63), with an eastward propagation signature at a similar phase speed as the convective anomalies (5 m s−1). The ozone anomalies on the intraseasonal time scale are about five times larger when lightning emissions of NOx are included in the simulation than when they are not. Nevertheless, large-scale advection is the primary driving force for the ozone anomalies associated with the MJO. The variability related to the MJO for ozone reaches up to 47% of the total variability (ranging from daily to interannual), indicating the MJO should be accounted for in simulating ozone perturbations in the tropics.

scholarly journals Biotic stress accelerates formation of climate-relevant aerosols in boreal forests

2015 ◽  
Vol 15 (21) ◽  
pp. 12139-12157 ◽  
Author(s):  
J. Joutsensaari ◽  
P. Yli-Pirilä ◽  
H. Korhonen ◽  
A. Arola ◽  
J. D. Blande ◽  
...  
Keyword(s):  
Boreal Forests ◽  
Large Scale ◽  
Transport Model ◽  
Cloud Condensation Nuclei ◽  
Fold Increase ◽  
Global Scale ◽  
Satellite Observations ◽  
Insect Outbreaks ◽  
Voc Emissions ◽  
Scale Modelling

Abstract. Boreal forests are a major source of climate-relevant biogenic secondary organic aerosols (SOAs) and will be greatly influenced by increasing temperature. Global warming is predicted to not only increase emissions of reactive biogenic volatile organic compounds (BVOCs) from vegetation directly but also induce large-scale insect outbreaks, which significantly increase emissions of reactive BVOCs. Thus, climate change factors could substantially accelerate the formation of biogenic SOAs in the troposphere. In this study, we have combined results from field and laboratory experiments, satellite observations and global-scale modelling in order to evaluate the effects of insect herbivory and large-scale outbreaks on SOA formation and the Earth's climate. Field measurements demonstrated 11-fold and 20-fold increases in monoterpene and sesquiterpene emissions respectively from damaged trees during a pine sawfly (Neodiprion sertifer) outbreak in eastern Finland. Laboratory chamber experiments showed that feeding by pine weevils (Hylobius abietis) increased VOC emissions from Scots pine and Norway spruce seedlings by 10–50 fold, resulting in 200–1000-fold increases in SOA masses formed via ozonolysis. The influence of insect damage on aerosol concentrations in boreal forests was studied with a global chemical transport model GLOMAP and MODIS satellite observations. Global-scale modelling was performed using a 10-fold increase in monoterpene emission rates and assuming 10 % of the boreal forest area was experiencing outbreak. Results showed a clear increase in total particulate mass (local max. 480 %) and cloud condensation nuclei concentrations (45 %). Satellite observations indicated a 2-fold increase in aerosol optical depth over western Canada's pine forests in August during a bark beetle outbreak. These results suggest that more frequent insect outbreaks in a warming climate could result in substantial increase in biogenic SOA formation in the boreal zone and, thus, affect both aerosol direct and indirect forcing of climate at regional scales. The effect of insect outbreaks on VOC emissions and SOA formation should be considered in future climate predictions.

Evaluation of tropospheric ozone residual measurements derived from TOMS-V9 and hyper-spectral total ozone algorithms

2021 ◽  
Author(s):  
Jerry Ziemke ◽  
Natalya Kramarova ◽  
Dave Haffner ◽  
Pawan Bhartia
Keyword(s):  
Tropospheric Ozone ◽  
Total Ozone ◽  
Model Simulation ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
Total Column Ozone ◽  
Hyper Spectral ◽  
Order Of Magnitude ◽  
Boundary Layer Ozone ◽  
Column Ozone

<p>The NASA TOMS V9 (TOMS-V9) total ozone retrieval algorithm is tested<br>for sensitvity to boundary-layer ozone and suitability to make daily<br>maps of tropospheric ozone residual (TOR).  Daily maps of TOR are<br>derived by differencing co-located MERRA-2 assimilated MLS<br>stratospheric column ozone (SCO) from total column ozone from the Aura<br>Ozone Monitoring Instrument (OMI).  The TOMS-V9 algorithm uses a few<br>discrete channels with an order of magnitude range in ozone<br>senstivity. We compare the TOR results from TOMS-V9 with results from<br>several hyper-spectral total ozone retrievals: GODFIT v4 (BIRA-IASB),<br>OMI-DOAS (KNMI), and total ozone from the SAO PROFOZ algorithm. We<br>compare all satellite-retrieved TOR with TOR derived from ozonesondes,<br>lidar, and the Goddard Modeling Initiative (GMI) model simulation.</p><p> </p><p> </p>

scholarly journals Error correlation between CO<sub>2</sub> and CO as constraint for CO<sub>2</sub> flux inversions using satellite data

2009 ◽  
Vol 9 (19) ◽  
pp. 7313-7323 ◽  
Author(s):  
H. Wang ◽  
D. J. Jacob ◽  
M. Kopacz ◽  
D. B. A. Jones ◽  
P. Suntharalingam ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Large Scale ◽  
Transport Model ◽  
Meteorological Data ◽  
Correlation Coefficients ◽  
Surface Fluxes ◽  
Satellite Observations ◽  
Carbon Surface ◽  
Chemical Transport Model ◽  
Error Correlation

Abstract. Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h GEOS-5 CTM forecasts of CO2 and CO columns for the same forecast time). We find strong error correlations (r2>0.5) between CO2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. We present a simple inverse modeling application to demonstrate that CO2-CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2-CO inversion vs. a CO2-only inversion.

scholarly journals Clouds, photolysis and regional tropospheric ozone budgets

2009 ◽  
Vol 9 (3) ◽  
pp. 13889-13916 ◽  
Author(s):  
A. Voulgarakis ◽  
O. Wild ◽  
N. H. Savage ◽  
G. D. Carver ◽  
J. A. Pyle
Keyword(s):  
Tropospheric Ozone ◽  
Large Scale ◽  
Transport Model ◽  
Regional Scale ◽  
Three Dimensional ◽  
Global Scale ◽  
Chemical Production ◽  
Chemical Transport Model ◽  
Photolysis Rates ◽  
Boundary Layer Ozone

Abstract. We use a three-dimensional chemical transport model to examine the shortwave radiative effects of clouds on the tropospheric ozone budget. In addition to looking at changes in global concentrations as previous studies have done, we examine changes in ozone chemical production and loss caused by clouds and how these vary in different parts of the troposphere. On a global scale, we find that clouds have a modest effect on ozone chemistry, but on a regional scale their role is much more significant, with the size of the response dependent on the region. The largest averaged changes in chemical budgets (±10–14%) are found in the marine troposphere, where cloud optical depths are high. We demonstrate that cloud effects are small on average in the middle troposphere because this is a transition region between reduction and enhancement in photolysis rates. We show that increases in boundary layer ozone due to clouds are driven by large-scale changes in downward ozone transport from higher in the troposphere rather than by decreases in in-situ ozone chemical loss rates. Increases in upper tropospheric ozone are caused by higher production rates due to backscattering of radiation and consequent increases in photolysis rates, mainly J(NO2). The global radiative effect of clouds on isoprene is stronger than on ozone. Tropospheric isoprene lifetime increases by 7% when taking clouds into account. We compare the importance of clouds in contributing to uncertainties in the global ozone budget with the role of other radiatively-important factors. The budget is most sensitive to the overhead ozone column, while surface albedo and clouds have smaller effects. However, uncertainty in representing the spatial distribution of clouds may lead to a large sensitivity on regional scales.

scholarly journals Error correlation between CO<sub>2</sub> and CO as constraint for CO<sub>2</sub> flux inversions using satellite data

2009 ◽  
Vol 9 (3) ◽  
pp. 11783-11810
Author(s):  
H. Wang ◽  
D. J. Jacob ◽  
M. Kopacz ◽  
D. B. A. Jones ◽  
P. Suntharalingam ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Large Scale ◽  
Transport Model ◽  
Meteorological Data ◽  
Co2 Flux ◽  
Surface Fluxes ◽  
Satellite Observations ◽  
Carbon Surface ◽  
Chemical Transport Model ◽  
Error Correlation

Abstract. Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a forward model such as a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. Model transport error is an important source of observational error. We investigate the potential of using CO satellite observations as additional constraints in a joint CO2–CO inversion to improve CO2 flux estimates, by exploiting the CTM transport error correlations between CO2 and CO. We estimate the error correlation globally and for different seasons by a paired-model method (comparing CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h CTM forecasts of CO2 and CO columns for the same forecast time). We find strong positive and negative error correlations (r2>0.5) between CO2 and CO columns over much of the world throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. Results from a testbed inverse modeling application show that CO2–CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2–CO inversion vs. a CO2–only inversion.

scholarly journals Ozone pollution during the COVID-19 lockdown in the spring 2020 over Europe analysed from satellite observations, in situ measurements and models

2021 ◽  
Author(s):  
Juan Cuesta ◽  
Lorenzo Costantino ◽  
Matthias Beekmann ◽  
Guillaume Siour ◽  
Laurent Menut ◽  
...  
Keyword(s):  
Large Scale ◽  
Transport Model ◽  
Surface Ozone ◽  
In Situ Measurements ◽  
Satellite Observations ◽  
Emission Inventories ◽  
Ozone Pollution ◽  
Chemistry Transport Model ◽  
Near Surface

Abstract. We present a comprehensive study integrating satellite observations of ozone pollution, in situ measurements and chemistry transport model simulations for quantifying the role of anthropogenic emission reductions during the COVID-19 lockdown in spring 2020 over Europe. Satellite observations are derived from the IASI+GOME2 multispectral synergism, which provides particularly enhanced sensitivity to near-surface ozone pollution. These observations are first analysed in terms of differences between the average on 1–15 April 2020, when the strictest lockdown restrictions took place, and the same period in 2019. They show clear enhancements of near-surface ozone in Central Europe and Northern Italy, and some other hotspots, which are typically characterized by VOC-limited chemical regimes. An overall reduction of ozone is observed elsewhere, where ozone chemistry is limited by the abundance of NOx. The spatial distribution of positive and negative ozone concentration anomalies observed from space is in relatively good quantitative agreement with surface in situ measurements over the continent (a correlation coefficient of 0.55, a root-mean-squared difference of 11 ppb and the same standard deviation and range of variability). An average bias of ∼8 ppb between the two observational datasets is remarked, which can partly be explained by the fact the satellite approach retrieves partial columns of ozone with a peak sensitivity above the surface (near 2 km of altitude). For assessing the impact of the reduction of anthropogenic emissions during the lockdown, we adjust the satellite and in situ surface observations for withdrawing the influence of meteorological conditions in 2020 and 2019. This adjustment is derived from the chemistry transport model simulations using the meteorological fields of each year and identical emission inventories. This observational estimate of the influence of lockdown emission reduction is consistent for both datasets. They both show lockdown-associated ozone enhancements in hotspots over Central Europe and Northern Italy, with a reduced amplitude with respect to the total changes observed between the two years, and an overall reduction elsewhere over Europe and the ocean. Satellite observations additionally highlight the ozone anomalies in the regions remote from in situ sensors, an enhancement over the Mediterranean likely associated with maritime traffic emissions and a marked large-scale reduction of ozone elsewhere over ocean (particularly over the North Sea), in consistency with previous assessments done with ozonesondes measurements in the free troposphere. These observational assessments are compared with model-only estimations, using the CHIMERE chemistry transport model. For analysing the uncertainty of the model estimates, we perform two sets of simulations with different setups, differing in the emission inventories, their modifications to account for changes in anthropogenic activities during the lockdown and the meteorological fields. Whereas a general qualitative consistency of positive and negative ozone anomalies is remarked between all model and observational estimates, significant changes are seen in their amplitudes. Models underestimate the range of variability of the ozone changes by at least a factor 2 with respect to the two observational data sets, both for enhancements and decreases of ozone, while the large-scale ozone decrease is not simulated. With one of the setups, the model simulates ozone enhancements a factor 3 to 6 smaller than with the other configuration. This is partly linked to the emission inventories of ozone precursors (at least a 30 % difference), but mainly to differences in vertical mixing of atmospheric constituents depending on the choice of the meteorological model.

scholarly journals Development of the global atmospheric chemistry general circulation model BCC-GEOS-Chem v1.0: model description and evaluation

2020 ◽  
Vol 13 (9) ◽  
pp. 3817-3838
Author(s):  
Xiao Lu ◽  
Lin Zhang ◽  
Tongwen Wu ◽  
Michael S. Long ◽  
Jun Wang ◽  
...  
Keyword(s):  
General Circulation Model ◽  
Atmospheric Chemistry ◽  
Tropospheric Ozone ◽  
General Circulation ◽  
Climate Models ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Circulation Model ◽  
Satellite Observations ◽  
Model Description

Abstract. Chemistry plays an indispensable role in investigations of the atmosphere; however, many climate models either ignore or greatly simplify atmospheric chemistry, limiting both their accuracy and their scope. We present the development and evaluation of the online global atmospheric chemical model BCC-GEOS-Chem v1.0, coupling the GEOS-Chem chemical transport model (CTM) as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model (BCC-AGCM). The GEOS-Chem atmospheric chemistry component includes detailed tropospheric HOx–NOx–volatile organic compounds–ozone–bromine–aerosol chemistry and online dry and wet deposition schemes. We then demonstrate the new capabilities of BCC-GEOS-Chem v1.0 relative to the base BCC-AGCM model through a 3-year (2012–2014) simulation with anthropogenic emissions from the Community Emissions Data System (CEDS) used in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The model captures well the spatial distributions and seasonal variations in tropospheric ozone, with seasonal mean biases of 0.4–2.2 ppbv at 700–400 hPa compared to satellite observations and within 10 ppbv at the surface to 500 hPa compared to global ozonesonde observations. The model has larger high-ozone biases over the tropics which we attribute to an overestimate of ozone chemical production. It underestimates ozone in the upper troposphere which is likely due either to the use of a simplified stratospheric ozone scheme or to biases in estimated stratosphere–troposphere exchange dynamics. The model diagnoses the global tropospheric ozone burden, OH concentration, and methane chemical lifetime to be 336 Tg, 1.16×106 molecule cm−3, and 8.3 years, respectively, which is consistent with recent multimodel assessments. The spatiotemporal distributions of NO2, CO, SO2, CH2O, and aerosol optical depth are generally in agreement with satellite observations. The development of BCC-GEOS-Chem v1.0 represents an important step for the development of fully coupled earth system models (ESMs) in China.

Cropland carbon uptake delayed by 2019 U.S. Midwest floods

2020 ◽  
Author(s):  
Yi Yin ◽  
Branden Byrne ◽  
Junjie Liu ◽  
Paul Wennberg ◽  
Philipp Köhler ◽  
...  
Keyword(s):  
Large Scale ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Gross Primary Production ◽  
Early Summer ◽  
Satellite Observations ◽  
Mitigation Strategies ◽  
Carbon Uptake ◽  
Vegetation Activity ◽  
The Impact

&lt;p&gt;While large-scale floods directly impact human lives and infrastructures, they also profoundly impact agricultural productivity. New satellite observations of vegetation activity and atmospheric CO&lt;sub&gt;2&lt;/sub&gt; offer the opportunity to quantify the effects of such extreme events on cropland carbon sequestration, which are important for mitigation strategies. Widespread flooding during spring and early summer 2019 delayed crop planting across the U.S. Midwest. As a result, satellite observations of solar-induced chlorophyll fluorescence (SIF) from TROPOspheric Monitoring Instrument (TROPOMI) and Orbiting Carbon Observatory (OCO-2) reveal a shift of 16 days in the seasonal cycle of photosynthetic activity relative to 2018, along with a 15% lower peak photosynthesis. We estimate the 2019 anomaly to have led to a reduction of -0.21 PgC in gross primary production (GPP) in June and July, partially compensated in August and September (+0.14 PgC). The extension of the 2019 growing season into late September is likely to have benefited from increased water availability and late-season temperature. Ultimately, this change is predicted to reduce the crop yield over most of the midwest Corn/Soy belt by ~15%. Using an atmospheric transport model, we show that a decline of ~0.1 PgC in the net carbon uptake during June and July is consistent with observed CO&lt;sub&gt;2&lt;/sub&gt; enhancements from Atmospheric Carbon and Transport - America (ACT-America) aircraft and OCO-2. This study quantifies the impact of floods on cropland productivity and demonstrates the potential of combining SIF with atmospheric CO&lt;sub&gt;2&lt;/sub&gt; observations to monitor regional carbon flux anomalies.&lt;/p&gt;

scholarly journals Tropospheric ozone variability in the tropics from ENSO to MJO and shorter timescales

2015 ◽  
Vol 15 (14) ◽  
pp. 8037-8049 ◽  
Author(s):  
J. R. Ziemke ◽  
A. R. Douglass ◽  
L. D. Oman ◽  
S. E. Strahan ◽  
B. N. Duncan
Keyword(s):  
Tropospheric Ozone ◽  
Large Scale ◽  
Climate Model ◽  
Transport Model ◽  
Southern Oscillation ◽  
Longwave Radiation ◽  
Chemical Transport Model ◽  
Enso Variability ◽  
Earth Observing System ◽  
The Tropics

Abstract. Aura OMI and MLS measurements are combined to produce daily maps of tropospheric ozone beginning October 2004. We show that El Niño-Southern Oscillation (ENSO) related inter-annual change in tropospheric ozone in the tropics is small in relation to combined intra-seasonal/Madden–Julian Oscillation (MJO) and shorter timescale variability by a factor of ~ 3–10 (largest in the Atlantic). Outgoing longwave radiation (OLR), taken as a proxy for convection, suggests that convection is a dominant driver of large-scale variability of tropospheric ozone in the Pacific from inter-annual (e.g., ENSO) to weekly periods. We compare tropospheric ozone and OLR satellite observations with two simulations: (1) the Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) that uses observed sea surface temperatures and is otherwise free-running, and (2) the NASA Global Modeling Initiative (GMI) chemical transport model (CTM) that is driven by Modern Era Retrospective-Analysis for Research and Applications (MERRA) analyses. It is shown that the CTM-simulated ozone accurately matches measurements for timescales from ENSO to intra-seasonal/MJO and even 1–2-week periods. The CCM simulation reproduces ENSO variability but not shorter timescales. These analyses suggest that a model used to delineate temporal and/or spatial properties of tropospheric ozone and convection in the tropics must reproduce both ENSO and non-ENSO variability.

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